Volume 10 Number 2 (Apr. 2020)
Home > Archive > 2020 > Volume 10 Number 2 (Apr. 2020) >
IJBBB 2020 Vol.10(2): 74-83 ISSN: 2010-3638
doi: 10.17706/ijbbb.2020.10.2.74-83

Analysis of Clustering Fragmented Protein Bond Angles

Justin S. Diamond
Abstract—The desire for accurate protein prediction algorithms has been a hallmark of computational biology achievements. Still, better algorithms and methodologies can achieve even greater success with implication across a diverse range of biological and medicinal fields such as protein function inference. Accurate prediction methods rely heavily on sequence similarity, however structure is more evolutionary conserved, i.e. structure is an alternate characteristic for ancestral relationships between proteins. The premise of this work is that similar structural features will be clustered together, which may show a unique amino acid and secondary structure (SS) distribution, which can be, incorporated into HMMs for SS prediction and protein function inference algorithms. With structural-evolutionary relationship in mind, I propose a methodology for ‘structure’ based SS prediction methods using HMM and k-mean and fuzzy k -means fragmented protein clusters. When fragment distributions were incorporated into HMMs, the average accuracy increased by 1 percent but showed an increase in accuracy of up to 13 percent for particular sequences. The HMM results were not so promising, however the clustering of protein structure fragments by C-alphas bond angles shows to be a useful length-independent metric for inferring functional relationships between proteins.

Index Terms—Protein structure, secondary structure, protein function, k-means, UPGMA.

The author is with Boston University Department of Bioinformatics, Boston, MA, USA (email: J3tkd@bu.edu).

Cite: Justin S. Diamond, "Analysis of Clustering Fragmented Protein Bond Angles," International Journal of Bioscience, Biochemistry and Bioinformatics vol. 10, no. 2, pp. 74-83, 2020.

Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

General Information

ISSN: 2010-3638 (Online)
Abbreviated Title: Int. J. Biosci. Biochem. Bioinform.
Frequency: Quarterly 
DOI: 10.17706/IJBBB
Editor-in-Chief: Prof. Ebtisam Heikal 
Abstracting/ Indexing:  Electronic Journals Library, Chemical Abstracts Services (CAS), Engineering & Technology Digital Library, Google Scholar, and ProQuest.
E-mail: ijbbb@iap.org
  • Jun 22, 2020 News!

    IJBBB Vol 10, No 3 has been published online! [Click]

  • Apr 02, 2020 News!

    The papers published in Vol 10, No 2 have all received dois from Crossref [Click]

  • Mar 25, 2020 News!

    IJBBB Vol 10, No 2 has been published online!  [Click]

  • Dec 13, 2019 News!

    The papers published in Vol 10, No 1 have all received dois from Crossref [Click]

  • Nov 29, 2019 News!

    IJBBB Vol 10, No 1 has been published online!  [Click]

  • Read more>>